Cargando…

Biochemical Characterization of Mouse Retina of an Alzheimer’s Disease Model by Raman Spectroscopy

[Image: see text] The presence of biomarkers characteristic for Alzheimer’s disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the...

Descripción completa

Detalles Bibliográficos
Autores principales: Stiebing, Clara, Jahn, Izabella J., Schmitt, Michael, Keijzer, Nanda, Kleemann, Robert, Kiliaan, Amanda J., Drexler, Wolfgang, Leitgeb, Rainer A., Popp, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581290/
https://www.ncbi.nlm.nih.gov/pubmed/32991138
http://dx.doi.org/10.1021/acschemneuro.0c00420
Descripción
Sumario:[Image: see text] The presence of biomarkers characteristic for Alzheimer’s disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the present study, retinas of a double transgenic mouse model, that expresses a chimeric mouse/human amyloid precursor protein and a mutant form of human presenilin 1, and corresponding control group were subjected to ex vivo Raman imaging. The Raman data recorded on cross sections of whole eyes highlight the layered structure of the retina in a label-free manner. Based on the Raman information obtained from en face mounted retina samples, a discrimination between healthy and Alzheimer’s disease retinal tissue can be done with an accuracy of 85.9%. For this a partial least squares-linear discriminant analysis was applied. Therefore, although no macromolecular changes in form of, i.e., amyloid beta plaques, can be noticed based on Raman spectroscopy, subtle biochemical changes happening in the retina could lead to Alzheimer’s disease identification.